Noyce Conference Room
Seminar
US Mountain Time
Speaker:
Tina Eliassi-Rad
Our campus is closed to the public for this event.
Tune in for the live stream on YouTube or Twitter.
Abstract: As the use of machine learning (ML) algorithms in network science increases, so do the problems related to explainability, transparency, fairness, privacy, and robustness, to name a few. In this talk, I will give a brief overview of the field and present recent work from my lab on the (in)stability and explainability of node embeddings, attacks on ML algorithms for graphs, and equality in complex networks.
Speaker
Tina Eliassi-RadProfessor, Computer Science, Northeastern University; Science Steering Committee Member + External Professor at SFISFI Host:
Cris Moore